diff --git a/intention-classify/training/train.py b/intention-classify/training/train.py
index 422e16c..dd7d946 100644
--- a/intention-classify/training/train.py
+++ b/intention-classify/training/train.py
@@ -88,7 +88,7 @@ def main():
 
     tokenizer = AutoTokenizer.from_pretrained(model_name)
     data = load_data("data.json")
-    class_to_idx, _ = create_class_mappings(data)
+    class_to_idx, idx_to_class = create_class_mappings(data)
     embedding_map = torch.load("token_id_to_reduced_embedding.pt")
     dataset = preprocess_data(data, embedding_map, tokenizer, class_to_idx)
     train_data, _ = train_test_split(dataset, test_size=0.2)
@@ -143,6 +143,12 @@ def main():
         },
         opset_version=11,
     )
+    meta = {
+        "idx_to_class": idx_to_class,
+        "threshold": 0
+    }
+    with open('NLU_meta.json', 'w') as f:
+        json.dump(meta, f)
 
 
 if __name__ == "__main__":
diff --git a/translate/validation/LLMtrans.py b/translate/validation/LLMtrans.py
index 9d06a1a..03c979b 100644
--- a/translate/validation/LLMtrans.py
+++ b/translate/validation/LLMtrans.py
@@ -2,6 +2,7 @@ from openai import OpenAI
 import argparse
 import os
 from dotenv import load_dotenv
+from tqdm import tqdm
 
 def translate_text(text, client, model_name, temp):
     messages = [
@@ -37,7 +38,7 @@ with open(input_file, "r") as f:
     src_lines = f.readlines()
 
 
-for line in src_lines:
+for line in tqdm(src_lines):
     result = translate_text(line, client, model, temp)
     with open(output_file, 'a') as f:
         f.write(result + '\n')